Comparison study of P-spline and univariate additive model (CUBIC smoothing spline) in time-series prediction
Özet
Smoothing splines used in many nonparametric problems to make a good approximation for smoothed functions in recent years. It is discussed two nonparametric techniques called P-spline and univariate additive model (cubic smoothing spline). In this study we made a comparison between P-splines and univariate additive model (cubic smoothing spline) for forecasting performance. To demonstrate comparison between these techniques we used a data set of exchange rate of Turkish Liras (TL)/Euro during 2005-2009 years and Gold Price during 2000-2009 years. Empirical results show that the P-spline model outperforms univariate additive model (cubic smoothing spline)
